Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

This dataset contains Registered Motor Vehicles in India for 1951-2019. Data from the Ministry of Road Transport and Highways. Follow datasource.kapsarc.org for timely data to advance energy economics research.Note: ‘Other vehicles’ include tractors, trailers, three wheelers (passenger vehicles)/LMV and other miscellaneous vehicles which are not classified separately.Note: 2017 results published as percentages and it has been converted to numbers by multiplying total vehicles with each percentage.

Water quality data for Lakes and ponds in India distributed by state.

This database contains information about India's Power Sector Review for 2000-2012.The database is a collection of primary and secondary data on the Indian power sector, collected at the utility and state levels. It covers 87 power utilities and 29 states and spreads over the years 2003 to 2011 across dimensions such as operational and financial performance, market structure, implementation of reforms and corporate and regulatory governance.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Data bout Vehicle Registrations in different cities and states

This datasets contains information about India's Category-Wise Automobiles Production for 2000 - 2016. Data from Ministry of Statistics and Programme Implementation, Government of India.Notes:* Vans are included in Passenger Cars

This dataset includes specimens originating from India in the collections at the Natural History Museum at the University of Oslo (NHM-UiO).

Animals: The mammal collection includes 108 specimens (mounted animals, skulls or skins, sometimes from the same individuals) from ‘India’. Insofar these are dated at all, they originate from the 19th century. No further collecting information is preserved. These data are already available from the GBIF portal (and not included in this dataset). Oslo has 1027 bird specimens from India, both skins and mounted and demounted specimens. These are either not dated or originate from the 19th century or the first half of the 20th century. Locality is sometimes recorded at the region or district level, with relatively many specimens from Darjeeling. More detailed collecting data are missing. Most have been collected by Englishmen, some of whom have had an important role in Indian ornithology. These skins may therefore be of particular historical value. Notable are 295 skins labeled as being collected by ‘Blyth’. This name most likely refers to the English zoologist Edward Blyth (1810 –1873), who was one of the founders of zoology in India (cf. Wikipedia lemma Edward Blyth). Another known name is Henry Seebohm (1832-1895), to whom twelve skins are attributed (misspelled in one case as Subohm). The bird data are not yet published in GBIF. The fish collection contains 34 databased specimens. The Staphylinidae beetle collection includes 508 specimens from India which are not yet identified to species level. The Hymenoptera collection includes 130 pinned specimens originating from the collection of Charles Thomas Bingham (1848-1908). These have been collected in Sikkim. In addition there are 7 Hymenoptera and 1 Orthoptera originating from the Deinboll collection, all labelled Trankebar. Some of these may represent types of taxa described by J.C. Fabricius (1745-1808). These collections are not yet digitised. There are virtually no Lepidoptera or Diptera from India in Oslo. Finally, the museum holds circa 10 crustacean specimens and 3 molluscs.

Plants: There is a small digitised collection of 89 vascular plants from Himachal Pradesh and Maharashtra provinces. These were deposited by the Indian student B. Natarajan who studied in Oslo in the 1990s. In addition, the older vascular plant type collection in Oslo has been digitised. This includes 12 older type specimens from India. Most of the herbarium has not been digitised, however. It may contain between 5 000 and 10 000 specimens from India. These are currently difficult to locate as the herbarium is organised in taxonomic rather than geographic units. The museum intends to digitise the herbarium at a level that would enable the retrieval of taxa per continent or even per country. This enterprise is still in the planning phase, however. Likewise the bryophyte and algae collections might contain material from India, but this can only be retrieved after digitisation. Some of these records are published to GBIF as a separate dataset. Oslo probably holds no Indian fungi. The digitisation of the Oslo lichen herbarium is ongoing. Currently 34 specimens from India are visible in the GBIF portal (and not included i this dataset). This number may increase to circa 100 once the entire lichen herbarium is digitised. Most of these have been collected after 1950 and have rather complete collecting data. The botanical garden in Oslo has 6 living plants originating from India.

This dataset contains the yearwise operational statistics of the MCA21 portal.

Link Function: information

Documentation

Description and codebook for subset of harmonized variables:

Section 2

Guide to datasets:

Full Project Name: The Impact of Mother Literacy and Participation Programs on Child Learning in India

Unique ID: 458

PIs: Rukmini Banerji, James Berry, Marc Shotland

Location: Indian states of Bihar and Rajasthan

Sample: Around 9,000 households in 480 villages

Timeline: 2010 to 2012

Target Group: Children Parents Rural population Women and girls

Outcome of Interest: Employment, Student learning ,Women’s/girls’ decision-making, Gender attitudes and norms

Intervention Type: Early childhood development, Tracking and remedial education, Empowerment training

Associated publications: https://www.aeaweb.org/articles?id=10.1257/app.20150390

More information: https://www.povertyactionlab.org/evaluation/impact-mother-literacy-and-participation-programs-child-learning-india

Dataverse: Banerji, Rukmini; Berry, James; Shotland, Marc, 2017, “The Impact of Maternal Literacy and Participation Programs: Evidence from a Randomized Evaluation in India”, https://doi.org/10.7910/DVN/19PPE7, Harvard Dataverse, V1

Section 3

Survey instrument:

Testing tools:

Section 4

Survey instrument:

Testing tools:

Section 5

No associated survey instrument

Section 6

This dataset was created on 2021-10-06 20:35:41.921 by merging multiple datasets together. The source datasets for this version were:

Maternal Literacy in India Baseline: Modified from ml_merged : contains data with variables only from baseline surveys

Maternal Literacy in India Endline: Modified from ml_merged : contains data with variables only from endline surveys

Maternal Literacy in India Raw Administrative Statistics: ml_admin_stats_raw: Contains administrative statistics from the 2011 census and aser surveys used in online Appendix Table 1 in the paper; this is merged with some of the survey data to create ml_admin_stats

Analysis of ‘Weather Data in India’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mahendran1/weather-data-in-india-from-1901-to-2017 on 30 September 2021.

--- Dataset description provided by original source is as follows ---

Context

This dataset contain mean temperature in india from 1901 to 2017

Content

Weather data collected from the government data portal. It contains month wise mean weather all over India.

Acknowledgements

The data was retrieved from the website https://data.gov.in/.

--- Original source retains full ownership of the source dataset ---

Contains data from the DHS data portal. There is also a dataset containing India - National Demographic and Health Data on HDX.

The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.

List of India Solar policy documents

Visit this link for solar atlas. Visit this link for policies details

Related KAPSARC Publication

Periodic assessment of dynamic ground water resources of the entire country. Contains Ground water situation and reports for all states and districts in the state, and at block level in the state. Some explainers: 1. Water measurement is in ham (cubic hectare meters) 2. Classification: Safe: < 60% of GW being used, Semi-critical: 60-90% of GW being used. Critical: 91-100% of GW being used. Overexploited: >100% being used. Saline: Water is brackish/saline.

Abstract

The Ministry of Human Resource Development (MHRD) initiated an All India Survey on Higher Education (AISHE) to build a robust database and to assess the correct picture of higher Education in the country. The main objectives of the survey was to (1) - identify & capture all the institutions of higher learning in the country, (2) - Collect the data from all the higher education institutions on various aspects of higher education.

Documentation

Please visit data.gov.in and/or contact Dr N Saravana Kumar.

Methodology

Data is being collected annually since 2011 on the following broad items

• Institution’s Basic Details
• Teacher’s Details
• Details of Non-Teaching Staff
• Programme conducted under various Faculties/Schools & Departments/Centres
• Students enrolled in these Programme
• Examination result of terminal year of each Programme
• Financial Information such as Receipt and Expenditure under various heads
• Availability of Infrastructure
• Scholarships, Loans & Accreditation

%3C!-- --%3E

Data is collected by inviting institutions of higher education to upload information. Around 900 universities, 40.000 colleges and 10.00 stand alone institutions are invited to respond annually (all institutions of higher education in India).

Section 7

Survey instruments:

Section 9

Survey instruments:

Section 8

Survey instrument:

Section 14

Survey instrument:

Section 15

Survey instrument:

Section 16

Survey instrument:

Section 4

Survey instruments:

Section 6

Survey instrument:

Section 3

Survey instruments:

Section 2

Description and codebook for subset of harmonized variables:

Section 13

Survey instrument:

Documentation

Full Project Name: Impact of Female Leadership on Aspirations and Educational Attainment for Teenage Girls in India

Unique ID: 498

PIs: Lori Beaman, Esther Duflo, Rohini Pande, Petia Topalova

Location: Birbhum District, West Bengal, India

Sample: 495 villages

Timeline: 2006 to 2007

Target Group: Parents Men and boys Rural population Women and girls Youth

Outcome of Interest: Discrimination Enrollment and attendance Women’s/girls’ decision-making Self-esteem/self-efficacy Aspirations Gender attitudes and norms

Associated publications: http://science.sciencemag.org/content/335/6068/582

More information: https://www.povertyactionlab.org/evaluation/impact-female-leadership-aspirations-and-educational-attainment-teenage-girls-india

Dataverse: Lori Beaman; Raghabendra Chattopadhyay; Esther Duflo; Rohini Pande; Petia Topalova, 2012, “Powerful women and aspirations in India”, https://doi.org/10.7910/DVN/O3UKFO, Harvard Dataverse, V3.

Section 5

Survey instrument:

Section 10

Survey instrument:

Section 17

This dataset was created on 2021-10-06 20:34:42.626 by merging multiple datasets together. The source datasets for this version were:

Powerful Women in India Adult Survey: Adult survey data, excluding section F5 on education; Only one round of data collection

Powerful Women in India Adult Education: Adult survey data from section F5 on education; Only one round of data collection

Powerful Women in India:

Powerful Women in India Facilities Anganwadi: Data collected from facilities survey on school facility quality only from the Anganwadi section

Powerful Women in India Facilities Math Test: Data collected from facilities survey on school facility quality only from the Math Test section

Powerful Women in India Facilities School Details: Data collected from facilities survey on school facility quality only from the School Details section

Powerful Women in India Household Roster: Data collected from household survey section A1 - household roster

Section 11

Survey instrument:

Section 12

This dataset was created on 2021-10-06 18:52:27.489 by merging multiple datasets together. The source datasets for this version were:

Powerful Women in India Facilities Survey: Data collected from facilities survey on school facility quality, excluding the following sections: -Anganwadi -Math test -Reading test -School Details

Powerful Women in India Facilities Reading Test: Data collected from facilities survey on school facility quality only from the Reading Test section

Powerful Women in India Household Survey: Data collected from household survey, excluding section A1

Powerful Women in India Participatory Resource Appraisal: Data from the assessment of village resources through a participatory resource appraisal exercise

Powerful Women in India Pradhan Survey: Data from current and previous Pradhans and their spouses about economic condition and political activities

Powerful Women in India Pradhan Seats Reserved for Women: Data at community/village level regarding current and previous Pradhan seats

Powerful Women in India Teenager Survey: Data from teenagers interviewed (children aged 11-16 years)

Documentation

Description and codebook for subset of harmonized variables:

Section 3

Survey instrument:

Section 9

Survey instrument:

Section 11

Survey instrument:

Section 16

Survey instrument:

Section 17

Survey instrument:

Section 13

Survey instrument:

Section 14

Survey instrument:

Section 21

Survey instrument:

Section 24

Survey instrument:

Section 18

Survey instrument:

Section 25

Survey instrument:

Section 28

No associated survey instrument

Section 2

Guide to datasets:

Full Project Name: Providing Health Insurance through Microfinance Networks in Rural Karnataka, India

Unique ID: 55

PIs: Abhijit Banerjee, Esther Duflo, Richard Hornbeck

Location: Rural Karnataka, India

Sample: 201 villages

Timeline: 2006 to 2010

Target Group: Rural population

Intervention Type: Credit, Insurance

Dataverse: Banerjee, Abhijit; Duflo, Esther; Hornbeck, Richard, 2015, “SKS Microfinance and Health Insurance”, https://doi.org/10.7910/DVN/PFCEVX, Harvard Dataverse, V2

Associated publications:

More information: https://www.povertyactionlab.org/evaluation/providing-health-insurance-through-microfinance-networks-rural-karnataka-india

Major health events survey:

Section 19

This dataset was created on 2021-10-06 18:50:26.783 by merging multiple datasets together. The source datasets for this version were:

SKS Microfinance India Household Health Events and Expenditures Baseline: - hh_master_e_PUBLISH.dta: HH Survey Module E: Health Events and Expenditures

SKS Microfinance India Household Survey Module A1 Endline: - household_A1_PUBLISH: Household Survey Module A1: Household Composition

SKS Microfinance India Household Survey Module B1 Endline: - household_B1_PUBLISH: Household Survey Module B1: Household Characteristics

SKS Microfinance India Household Survey Module B2 Endline: - household_B2_PUBLISH: Household Survey Module B2: Household Characteristics

SKS Microfinance India Household Survey Module C1 Endline: - household_C1_PUBLISH: Household Survey Module C1: Household Income

SKS Microfinance India Household Survey Module C2 Endline: - household_C2_PUBLISH: Household Survey Module C2: Household Income

SKS Microfinance India Household Survey Module C3 Endline: - household_C3_PUBLISH: Household Survey Module C3: Household Income

SKS Microfinance India Household Survey Module C4 Endline: - household_C4_PUBLISH: Household Survey Module C4: Household Income

SKS Microfinance India Household Survey Module D1 Endline: - household_D1_PUBLISH: Household Survey Module D1: Household Expenditures

SKS Microfinance India Household Survey Module D2 Endline: - household_D2_PUBLISH: Household Survey Module D2: Household Expenditures

SKS Microfinance India Household Survey Module D3 Endline: - household_D3_PUBLISH: Household Survey Module D3 & D4: Household Expenditures

SKS Microfinance India Household Survey Module E0 Endline: - household_E0_PUBLISH: Household Survey Module E0: Health

SKS Microfinance India Household Survey Module E1 Endline: - household_E1_PUBLISH: Household Survey Module E1 & E2 & E3: Health

SKS Microfinance India Household Survey Module E4 Endline: household_E4_PUBLISH: Household Survey Module E4: Health

SKS Microfinance India Household Baseline: - hh_master_PUBLISH.dta: HH Survey Module A: Household Composition; HH Survey Module B: Household Characteristics; HH Survey Module C: Household Income; HH Survey Module D: Household Expenditures; HH Survey Module E: Health

Section 20

No associated survey instrument

Section 23

Survey instrument:

Section 6

Survey instrument:

Section 4

Survey instrument:

Section 5

Survey instrument:

Section 29

This dataset was created on 2021-10-06 20:36:55.480 by merging multiple datasets together. The source datasets for this version were:

SKS Microfinance India 1:

SKS Microfinance India Village Treatment: Treatment assignment by village ("clean_treatment_PUBLISH.dta")

Section 7

Survey instrument:

Section 12

Survey instrument:

Section 15

Survey instrument:

Section 10

Survey instrument:

Section 8

Survey instrument:

Section 22

Survey instrument:

Section 26

Survey instrument:

Section 27

This dataset was created on 2021-10-06 20:36:24.646 by merging multiple datasets together. The source datasets for this version were:

SKS Microfinance India Adult Baseline: - adult_master_PUBLISH.dta: Adult Survey Module C: Perso

This data set contains four data files in text format (.txt). Three files provide above- and below-ground productivity data for three derived savannas on the Vindhyan plateau in northern India from 1986 to 1989, one file for each of three treatments. Each study site (Ranitali, Hathinala, Telburva) contains three treatment areas: ungrazed; grazed annually for 30-40 years; and grazed but temporarily fenced for 2-6 years prior to the study. The fourth file provides climate data from a weather station at Daltonganj, India, for the period 1893-1990. Monthly dynamics of above- and below-ground biomass were measured by harvest methods in each treatment area at each site for two annual cycles (1986/1987 and 1987/1988). Additional above-ground peak biomass data (live shoot + dead shoot) for October 1988 from ungrazed and grazed plots represent the 1988/1989 annual cycle.Annual above-ground net primary production (ANPP) was estimated using trough-peak analysis of increments in live biomass, standing dead matter, and litter. Annual below-ground production (BNPP) was estimated from biomass increments combined with root in-growth studies. Mean ANPP for the ungrazed treatment areas on the three sites ranged from 377 to 664 g/m2/yr over the 1986 to 1989 period. Mean BNPP in the same areas was estimated at 510 and 727 g/m2/yr for 1986/1987 and 1987/1988, respectively. Mean total ungrazed NPP (ANPP + BNPP) was estimated at 1,082 and 1,391 g/m2/yr for 1986/1987 and 1987/1988, respectively.Revision Notes: The NPP data for the temporarily fenced grassland sites for the 1987/1988 annual cycle have been revised to correct previously reported BNPP estimates. Please see the Data Set Revisions section of this document for detailed information.

This dataset contains historical data from WHO's data portal.